Motion blur in photographed images, offline rendering, and in real-time graphics provides the viewer with a sense of motion direction and also reduces temporal aliasing. When motion blur is present, the shadows of moving objects should be motion blurred as well. However, while shadow rendering has received a lot of attention in the research community for static scenes, rendering of motion blurred shadows has remained relatively unexplored.
Accumulation buffering can be used to generate motion blurred shadows, but the algorithm only supports using identical sample times for all pixels in the shadow map. This often shows up as banding artifacts unless many full-screen passes are used, and that is often not possible within the time budget for real-time rendering. Instead, one can use stochastic sampling when generating the shadow map. This removes banding artifacts by allowing samples to have unique times, but the resulting image is often too noisy at affordable sample rates. Deep shadow mapping is a technique originally intended for rendering shadows for hair, smoke, fur, etc. Motion blurred shadows can also be generated using deep shadow maps, however, they are only correct when the receiving object is static.
In the presence of motion blur, the problem of computing accurate shadows in a graphics engine is very difficult. Currently, the resulting shadows are often highly approximate, lack blur or are overly noisy. This is a consequence of the fact that the visibility integral (what light reaches a certain point from the light sources in the scene) needs to be evaluated both spatially and temporally. A common approximation of this integral is to use Monte Carlo sampling, wherein the scene is sampled at a certain number of spatial and temporal locations. However, unless a large number of samples are used, the shadows will be very noisy.